3D Fashion Deep Dive 05: AI in 3D Fashion
Where It Actually Fits Into Fashion Workflows
If you’ve been following this series, we’ve been building up moment and now we are in the meat of it…
We started with the big picture of why 3D fashion matters right now.
Then we walked through the history, the software stack, and the real workflows of people actually doing this work day-to-day, and the nuisances of draping in these workflows.
Now it’s time to discuss the topic that seems to come up in any conversation about creative workflows: AI.
Specifically, which AI tools are currently used in 3D fashion workflows, and where do they deliver real value? Because if you listen to the hype, you’d think fashion design is one prompt away from full automation and we are all doomed to a life as some pet for our well-dressed robotic overlords.
But if you talk to people inside the industry, you get a very different story.
Let’s break it down.
AI for Early Ideation and Concept Development
This is where AI shows up first, loudest, and most visibly.
And honestly?
This is one of the places where it actually works. Because for all it’s six-fingered, dead-eyed sloppiness, AI is undeniably a good tool for generating ideas, directions, and visual starting points. It helps designers explore silhouettes, proportions, materials, and vibes before anything becomes technical.
Common tools you’ll see here:
Vizcom
Google’s Nano Banana
Adobe Firefly
Midjourney
Stable Diffusion
…and I am sure there are 5 more that crept up while I was writing this article…
How fashion teams use this:
They’re not using AI to design garments. They’re using it to start conversations.
Mood boards. Concept exploration. Early silhouettes. Directional imagery. Visual shorthand for ideas that would otherwise take days of sketching and back-and-forth.
What AI is not doing here:
Creating production-ready garments
Replacing patternmaking
Replacing fit logic
These images are references, not assets.
AI accelerates ideation, but the moment something needs to be real, measurable, or manufacturable, humans step in.
AI-Assisted Material Creation and Fabric Digitization
If there’s one area where AI is quietly doing real work, it’s materials. This isn’t the loud “text-to-material” type of workflows you might be thinking. But, more silent, under the hood type stuff.
This isn’t generative AI. It’s assistive AI.
Common tools:
Substance 3D Sampler
CLO fabric libraries
Browzwear FAB Analyzer
Here’s what’s happening:
Teams are scanning or photographing real fabrics and using AI-assisted tools to generate usable digital materials. Properties such as weave detail, roughness behavior, normal maps, and base color information can now be extracted much faster using AI-powered workflows.
This doesn’t remove the need for expertise. It just removes friction and allows creators to work faster.
This matters a lot because fabric behavior is huge. If the material is wrong, the drape is wrong. If the drape is wrong, the whole garment is wrong.
AI Inside 3D Garment Construction Tools
This same principle applies to some garment creation tools.
We’re talking about:
Smart defaults
Simulation stabilization
Pattern adjustment suggestions
Fit prediction
Auto-grading support
It helps designers move faster, make fewer mistakes, and iterate with confidence. But it does not design garments for them. The logic still comes from the pattern, the construction, and the designer’s intent.
AI for Visualization, Rendering, and Content Production
This uses generative AI to envision garments on people and in specific situations quickly. These might not be at the level of marketing content, but they are highly beneficial when preparing internal presentations or sales to other businesses. These aren’t advanced enough to fully represent your brand externally, but they're certainly up to the task of communicating ideas and helping sell your vision more effectively.
Common tools here:
Nano Banana
Photoshop + Firefly
Stable Diffusion (image-to-image)
Runway
Unreal Engine with AI-assisted workflows
These tools are often used after the garment exists.
Think:
Marketing imagery
Campaign visuals
Lookbooks
Social content
Background replacement
Motion enhancement
Again, these tools will hallucinate elements to the original design so they are not often of a high quality enough to be customer-facing content, but they are getting good enough to present the look of what the final vision will be.
AI for Fit Prediction and Virtual Try-On
This is the exciting category and often the most misunderstood.
Yes, AI-powered try-on and fit prediction tools are real…kind of.
Yes, brands are investing heavily here.
But this space is hard. Really hard.
It depends on:
Accurate garment simulation
Reliable body data
Consistent fabric behavior
Clean input assets
AI doesn’t replace any of that. It sits on top of it. When it works, it’s powerful. And it only works if all the upstream departments are humming and delivering high-quality digital twins complete with the metadata to empower this workflow.
But if the underlying data is bad, it falls apart fast.
This is why fit-focused AI is still evolving. It’s not a one-click solution but a layer that needs to be integrated into a highly advanced, currently developing system.
AI for Workflow, Asset, and Pipeline Automation
This is the least glamorous category and possibly the most valuable.
Common use cases:
Asset tagging
Version comparison
Metadata cleanup
Batch processing
Naming conventions
PLM and DAM enrichment
With thousands of SKUs (individual products) in various colors and in various regions around the world, keeping track of it all in management systems is difficult, painful, and tedious. I talk to a lot of companies in this space.
Some are thriving. Some are struggling. Some are highly advanced and some are just getting started. But the one thing they all have in common is a frustration with how they store, manage, and track their products.
This is where 3D artists with technical backgrounds absolutely shine.
If you come from VFX or games and know how to automate, script, or clean pipelines, this is gold in fashion. Many teams are still building these workflows for the first time and could use your expertise.
You know what should be done by humans and what can be automated or utilized by AI tools to streamline the system.
The Big Pattern (This Is the Part That Matters)
Here’s the throughline across all of this:
AI in 3D fashion is not replacing designers.
It’s not replacing simulation.
And it’s definitely not “one prompt to production.”
What it is doing:
Speeding up ideation
Reducing friction between steps
Assisting technical workflows
Making realism more scalable
Aiding the management of the entire process
AI amplifies good workflows.
It exposes bad ones.
If you already understand garments, materials, simulation, and pipeline thinking, AI makes you faster and more powerful. If you don’t, AI just makes mistakes faster.
And this is where 3D artists transitioning into fashion have a massive opportunity.
You already know how to think in systems.
You already understand data, realism, and iteration.
AI becomes a multiplier, not a crutch.
That’s the real story of AI in 3D fashion right now.
Not hype.
Not replacement.
Acceleration.
And we’re still early.
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Hello! Michael Tanzillo here. I am the Head of Technical Artists with the Substance 3D team at Adobe. Previously, I was a Senior Artist on animated films at Blue Sky Studios/Disney with credits including three Ice Age movies, two Rios, Peanuts, Ferdinand, Spies in Disguise, and Epic.
In addition to his work as an artist, I am the Co-Author of the book Lighting for Animation: The Visual Art of Storytelling and the Co-Founder of The Academy of Animated Art, an online school that has helped hundreds of artists around the world begin careers in Animation, Visual Effects, and Digital Imaging. I also created The 3D Artist Community on Skool and this newsletter.
www.michaeltanzillo.com
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